We performed a comparison between RapidMiner and SAS Predictive Analytics based on real PeerSpot user reviews.
Find out what your peers are saying about Alteryx, RapidMiner, SAP and others in Predictive Analytics."Scalability is not really a concern with RapidMiner. It scales very well and can be used in global implementations."
"The solution is stable."
"Using the GUI, I can have models and algorithms drag and drop nodes."
"The best part of RapidMiner is efficiency."
"The most valuable feature of RapidMiner is that it can read a large number of file formats including CSV, Excel, and in particular, SPSS."
"The documentation for this solution is very good, where each operator is explained with how to use it."
"It's helpful if you want to make informed decisions using data. We can take the information, tease out the attributes, and label everything. It's suitable for profiling and forecasting in any industry."
"The most valuable feature of RapidMiner is that it is code free. It is similar to playing with Lego pieces and executing after you are finished to see the results. Additionally, it is easy to use and has interesting utilities when preparing the data. It has a utility to automatically launch a series of models and show the comparisons. When finished with the comparisons you can select the best one, and deploy it automatically."
"The most valuable feature is its flexibility and the ability to integrate with SAS."
"The most valuable features are forecasting and reporting."
"I would like to see all users have access to all of the deep learning models, and that they can be used easily."
"I would like to see more integration capabilities."
"If they could include video tutorials, people would find that quite helpful."
"I think that they should make deep learning models easier."
"Many things in the interface look nice, but they aren't of much use to the operator. It already has lots of variables in there."
"RapidMiner would be improved with the inclusion of more machine learning algorithms for generating time-series forecasting models."
"The biggest problem, not from a platform process, but from an avoidance process, is when you work in a heavily regulated environment, like banking and finance. Whenever you make a decision or there is an output, you need to bill it as an avoidance to the investigator or to the bank audit team. If you made decisions within this machine learning model, you need to explain why you did so. It would better if you could explain your decision in terms of delivery. However, this is an issue with all ML platforms. Many companies are working heavily in this area to help figure out how to make it more explainable to the business team or the regulator."
"A great product but confusing in some way with regard to the user interface and integration with other tools."
"I think that this solution should be more compatible with other software, including open-source solutions."
"Technical support could be improved because they take too long to answer our queries."
Earn 20 points
RapidMiner is ranked 2nd in Predictive Analytics with 19 reviews while SAS Predictive Analytics is ranked 9th in Predictive Analytics. RapidMiner is rated 8.6, while SAS Predictive Analytics is rated 7.0. The top reviewer of RapidMiner writes "Offers good tutorials that make it easy to learn and use, with a powerful feature to compare machine learning algorithms". On the other hand, the top reviewer of SAS Predictive Analytics writes "Good forecasting, reporting, and data integrity, but it needs to be more user-friendly". RapidMiner is most compared with KNIME, Alteryx, Dataiku Data Science Studio, Tableau and Microsoft Azure Machine Learning Studio, whereas SAS Predictive Analytics is most compared with DataRobot and TIBCO Statistica.
See our list of best Predictive Analytics vendors.
We monitor all Predictive Analytics reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
